How GPT (not that one) could help fix our inflation problem

By Millie Muroi, Economics Writer

ChatGPT is not the answer to Australia’s productivity problem. At least, not yet.

But I asked ChatGPT what its chances were of productivity improving in Australia – if it was a betting man. The answer? 70 to 80 per cent.

Productivity growth excites economics nerds, like those at the Reserve Bank ... and just about no one else. But it matters for everything from your mortgage to the prices you pay at shops and the quality of your life.

Why? Because productivity growth means being able to make more with what we have, which is the best solution to the biggest economic issue of our time: inflation.

After all, there are two sides to this inflation problem: too much demand and too little supply. Instead of the Reserve Bank beating down our appetite for goods and services through ramping up interest rates, wouldn’t it be nice if businesses could simply produce more with the workers and equipment they already had, therefore keeping prices in check?

We could work longer hours and maybe even put our machines under more strain, but we can only do that for so long: it would be like trying to run a marathon at sprinting speed.

That doesn’t mean we should abandon all hope.

Instead, to curb price rises, and to lift our living standards over time, we need to improve productivity. Like a marathon runner improving their running technique, we need a way to get faster or better at what we do. A crucial way of doing this is through discovering and using new technology that helps us pump out more, or better quality, goods and services, in a way that can be maintained.

The most influential of these tools (those that have transformed the way we live) are called General-Purpose Technologies – or GPTs for short. The steam engine, cars, electricity and the internet all count as GPTs, because they were widely adopted and became crucial pieces of technology which dramatically yanked up our productivity.

We may not consciously think about it. But imagine what our lives would look like today without electricity, internet and cars. We would be slower, have much less information at our fingertips and would find it harder to work once the sun sets.

As Andrew Leigh points out in his book The Shortest History of Economics, the journey to create the electric bulb itself shows how our productivity has improved. In prehistoric times, producing as much light as a regular household lightbulb using wood fire would have taken our ancestors about 58 hours of foraging for wood. Today, it takes less than a second of work to earn enough to flick a household light bulb on for an hour.

ChatGPT is an example of a tool that could become a general-purpose technology. But the “GPT” in its name actually stands for “generative pre-trained transformer”: a fancy way of saying a piece of software trained using huge amounts of data to offer up human-like answers to questions like mine.

During the pandemic, there was a short-lived surge in the take-up of cloud computing (IT services that businesses can use without owning or running the physical servers, hard drives and networks required themselves). But generally, Australian businesses are behind the curve when it comes to adopting new technologies – and we don’t develop much of it ourselves.

That doesn’t mean we should abandon all hope. Instead, we need to think about the drivers of, and barriers to, adopting technologies such as cloud computing and artificial intelligence: two GPTs in the making.

Kim Nguyen and Jonathan Hambur at the Reserve Bank say these technologies could alter the way we do business. But knowing how to use and make the most of them also requires highly skilled and educated workers.

A website called ChatGPT is raising questions about the role of artificial intelligence in our education, work and relationships.

Nguyen and Hambur’s research involved trawling through the annual reports, job ads and earnings calls of Australian businesses to figure out how much workers’ and managers’ skills matter when it comes to successful adoption of GPTs.

Here’s what they found. Firms which had snagged a board member with experience in the IT industry were 30 percentage points more likely to adopt a GPT. While there were certainly businesses which took up GPT without a technologically skilled board member on their team, these firms generally failed to see much improvement in their profitability after putting a GPT in place.

Basically, having board members with relevant technological experience has been linked to more profitable use of GPT. Of course, the authors point out this could be because firms that appoint technology-savvy board members tend to be more focused on IT in the first place, and therefore more likely to be able to adopt GPT in a way that increases profitability.

But firms with technologically skilled board members were also more likely to look for workers with GPT skills, indicating those workers might also play an important role in profitable GPT adoption. Whatever the exact link, uptake of GPT is linked to higher demand for skilled workers, meaning education and training will be key to nailing the use of these technologies.

While the Reserve Bank’s toolkit is limited to setting interest rates (and, informally, jawboning) the less painful solution to getting inflation under control is to improve our productivity, and therefore the amount of goods and services to go around.

Productivity growth is difficult to measure, and quarter-to-quarter movements can be rocked by things that have little to do with anything. But it has flattened out in recent months, and without productivity growth to match, wages, which have begun to pick up in recent times, will worry the Reserve Bank and may build the case for the Reserve Bank to keep interest rates higher for longer.

ChatGPT has hit the headlines over the past year: from students using it in a bid to boost their marks and to some media companies relying on it to churn out AI-generated content. While it’s yet to join the ranks of coveted general-purpose technologies, ChatGPT is an example of innovation which could turn out to be a game-changer.

Right now, it’s an imperfect tool being put to use by an inexperienced user (me). But I asked ChatGPT if it could write a better opinion piece, and faster than I could. The answer? “I’d love to give it a try!” 

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The digital revolution may be returning us to hi-tech serfdom

On the longest of our long weekends, it’s good to have something different to think about. Try this. Could it be that the information revolution – big tech, big data, the internet and social media – is changing how the economy works in ways we’ve yet to understand and won’t like?

The world abounds with economists repeating their conventional wisdom about how the economy works and will keep on working. But one economist politician thinks that digitisation is changing the economy in ways that could lead us back to a new kind of feudalism.

He is Yanis Varoufakis, who lectured at Sydney University for some years before returning to Greece and briefly becoming its finance minister. He visited Australia earlier this month as a guest of the Australia Institute.

In the Middle Ages, feudalism was a system of reciprocal military and economic obligations running from the king to his land-owning lords, whose vassals managed their land worked by serfs.

In Varoufakis’s dystopian vision, the digital revolution, led by a few big technology companies – Meta (Facebook), Alphabet (Google), Apple, Amazon and Microsoft – is turning capitalism into “technofeudalism”. Hence the title of his book, Technofeudalism: What Killed Capitalism.

In the internet’s initial phase, it was characterised by open protocols and decentralised networking, focused on information sharing and communication.

Now, however, it has evolved towards more commercialised, centralised services, including social media, e-commerce and cloud computing. His metaphor for the changed parts of the economy is the “cloud”.

The capitalists – owners of physical capital - are being replaced by “cloudalists”: individuals or businesses that control the major digital platforms (such as the Facebook, Google and Twitter sites) and related infrastructure, which allows them to extract “cloud rent” from the consumers and businesses using their platforms.

“Fief” is the feudal word for land. But “cloud fiefs” are Varoufakis’s term for the digital domains and platforms controlled by the cloudalists. These can be specific services, apps or platforms where the cloudalists have significant control, allowing them to extract “cloud rent”.

This process is similar to the way feudal lords controlled land and extracted ordinary rent from those using it.

Economists use the word “rent” – economic rent – to mean prices people are required to pay in excess of the price a business (or a skilled worker) would require to keep them providing the good or service.

Why are sellers able to charge these higher prices? Because you can’t get that same thing anywhere else. Why do fans pay a fortune for tickets to a Taylor Swift concert? Because they don’t want to settle for some other singer.

So cloud rent is payments made by “cloud serfs” to cloudalists for the use of digital platforms and services. This rent is a form of income for cloudalists, derived from their control over these digital assets, rather than from the production or sale of conventional goods and services.

Thus, whereas capitalists seek to make a profit by selling goods and services, cloudalists seek extract rents from cloud serfs – the users and businesses that depend on the digital platforms and apps the cloudalists control.

Cloud serfs are akin to the serfs in feudal times, bound to the platforms and subject to their terms, often contributing their personal data or content while having limited autonomy and receiving fewer benefits.

Get that? The rent many serfs pay isn’t money, it’s their personal data about their purchasing habits and preferences, and their geographical movements, which can be of great value to businesses trying to sell them things.

Of course, cloud serfs aren’t to be confused with “cloud proles”. Huh? In Varoufakis’s vision, these are the people who work directly for the cloudalists such as Amazon. They’re often highly supervised, with little autonomy, and can even be managed by algorithms.

The modern equivalent of the lord of the manor’s “vassal” managers are the businesses that operate on the cloudalists’ digital platforms. They are subject to the cloudalists’ terms and conditions. While they may own their businesses, they must pay a portion of their earnings as rent to the platform owners and must adhere to their rules.

Getting past all these new names for things, a key point Varoufakis makes is the way the digital revolution has moved us from one-way advertising to two-way algorithms.

Although advertising could instil in us the desire to buy stuff we hadn’t formerly known we wanted, this is just a one-way street. With cloud-based, Alexa-like devices, the cloudalists can not only induce us to buy things, they can also modify our behaviour.

Knowing so much about our weaknesses, they can make us addicted to doing things that benefit them more than us – even just capturing our attention for protracted periods.

Varoufakis says algorithms have already replaced bosses in the transport, delivery and warehousing industries. Workers find themselves in a modernist nightmare: some entity that is incapable of human empathy allocates them work at a rate of its choosing before monitoring their response times.

This is no longer a market in any meaningful sense. Everything and everyone is intermediated (brought together) not by the disinterested invisible hand of the market, but by an algorithm that works for the cloudalist’s bottom line and dances exclusively to their tune.

Finally, Varoufakis argues that, thanks to all money created out of thin air by the rich world’s central banks during their resort to “quantitative easing” in the global financial crisis and then the pandemic, big tech was able to greatly expand its cloud capital without needing to borrow at great expense, sell large parts of its businesses to others, or generate large profits to pay for new capital stock.

Between 2010 and 2021, he says, the paper wealth of two men – Jeff Bezos and Elon Musk – that is, the market price of their shares – rose from less than $US10 billion to about $US200 billion each.

Even without the fancy jargon, this stuff is hard to get your head around. In 10 years’ time, we’ll know if it was fanciful or prophetic.

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How the digital world is getting better at measuring us up

These days we hear incessantly about “data”. The media is full of reports of new data about this or that, and there’s a new and growing occupation of data analysts and even data scientists. So, what is data, where does it come from, what are people doing with it, and why should I care?

Google “data” and you find it’s “facts and statistics collected together for reference or analysis”. The advent of computers has allowed businesses and governments to record, calculate, play with and store huge amounts of data.

Businesses have data about what goods and services they’re making, buying and selling, importing or exporting, and paying their workers, going back for 30 or 40 years.

Our banks have data about what we earn and what we spend it on, especially when we use a credit or debit card – or our phone – to pay for something.

Much of this data is required to be supplied to government agencies. If you ever go onto the Australia Taxation Office’s website to do your annual tax return, it will offer to “pre-fill” your return with stuff it already knows about your income from wages, bank interest and dividends.

Try it sometime. You’ll be amazed by how much the taxman knows and how accurate his data are.

Another dimension of the “information revolution” is how advances in international telecommunications – including via satellites – have allowed us to be in touch with people and institutions around the world in real-time via email and the web – news, entertainment, social media, whatever.

Last month, the Australian Statistician – aka the boss of the Australian Bureau of Statistics – Dr David Gruen, gave a speech outlining some of the ways these huge banks of “big data” about the economic activities of the nation’s businesses, workers, consumers and governments can be used to improve the way we measure the economy in all its aspects: employment, inflation, gross domestic product and the rest.

We’re getting more information and more accurate information, and we’re getting it much sooner than we used to. But we’re still in the early days of exploiting this opportunity to be better informed about what’s happening in the economy and to have better information to guide the government’s decisions about its policies to improve the economy’s performance.

Gruen starts by describing the Tax Office’s “single-touch” payroll system, software that automatically receives information about employees’ payments every time an employer runs its payroll program.

Not all employers have the software, but those who do account for more than 10 million of our 14 million employees.

Gruen says the arrival of the pandemic in early 2020 made access to this “rich vein of near real-time information” an urgent priority. The taxman pulled out the stops, and the stats bureau began receiving these data in early April 2020.

With a virus spreading through the land and governments ordering lockdowns and border closures, they couldn’t afford to wait a month or more to find out what was happening in the economy. Thus, the whole project of using big data to help measure the economy received an enormous kick along – here and in all the other rich economies.

So, in addition to the longstanding monthly sample survey of the labour force, we now have a new publication: Weekly Payroll Jobs and Wages Australia. These data allowed the econocrats—and the rest of us—to chart the dramatic collapse in jobs across the economy over the three weeks from mid-March 2020.

They show employment in the accommodation and food services industry falling by more than a quarter in just three weeks. Employment in the arts and recreation services industry fell by almost 20 per cent. By contrast, falls in utilities and education and training were minor.

The monthly labour force survey has a sample size of about 50,000 people, compared with the payroll program’s 10 million-plus people, meaning it provides information on far more dimensions of the workforce than the old way does.

So, the bureau’s access to payroll data taught it new ways of doing things. And the pandemic increased econocrats’ appetite for more info about the economy that was available in real-time.

With household consumption – consumer spending – accounting for about half of gross domestic product, improving the timeliness and detail of the data was a great idea.

So, in February 2022, the bureau released the first monthly household spending indicator using (note this) aggregated and de-identified data on credit and debit card transactions supplied by the major banks. This indicator provides two-thirds coverage of household consumption, compared with the less than one-third coverage provided by the usual survey of retail trade.

The bureau has also begun publishing a monthly consumer price index in addition to the usual quarterly index. This is possible because big data – in the form of data from scanners at checkout counters and data scraped from the websites of supermarket chains – is much cheaper to gather than the old way.

The bureau has also started integrating different but related sets of big data from several sources, so analysts can study the behaviour of individual consumers or businesses. It has developed two large integrated data assets.

The one for individuals links families and households with data sets on income and taxation, social support, education, health, migrants and disability.

The one for businesses links them with a host of surveys of aspects of business activity, income and taxation, overseas trade, intellectual property and insolvency.

The purpose is to allow analysts from government departments, universities or think tanks to shed light on policy problems from multiple dimensions.

For instance, one study showed that people over 65 who’d had their third COVID vaccination within the previous three months were 93 per cent less likely to die from the virus than an unvaccinated person.

But that’s just the tiniest example of what we’ll be able to find out.

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It's time for more sensible thinking on productivity

When will we tire of all the bulldust that’s talked in the name of hastening productivity improvement? We never do anything about it, but we do listen politely while self-appointed worthies – business people and econocrats, in the main – read us yet another sermon on the subject.

Trouble is, when the sermons come from big business – accompanied by 200-page reports with snappy titles – they boil down business lobby groups doing what lobby groups do: asking the government for special favours – aka “rent-seeking”.

You want higher productivity? It’s obvious: cut the company tax on big business, and give us a free hand to change our workers’ pay and conditions as we see fit.

When the sermons come from econocrats, they’re more like professional propagandising: calls for “reform” – often of the tax system – that are usually theory-driven and lacking empirical evidence that they really would have much effect on productivity.

What we get in place of genuine empiricism is modelling results. Models are a mysterious combination of mathematised theory, sprinkled with ill-researched estimates of elasticity and such like.

We’ve become so inured to all this sermonising that we’ve ceased to notice something strange: although in a market economy it’s the behaviour of business that determines how much productivity improvement we do or don’t get, any lack of improvement is always attributed to the government’s negligence.

This is where the business rent-seekers and the econocrat propagandists are agreed. The econocrats willingness to point at the government comes from the biases in their neoclassical theory, which assumes, first, that businesses always respond rationally to the incentives they face and, second, that government intervention in markets is more likely to make things worse than better.

Big business is happy to use this ideology to hide its rent-seeking. (If you wonder why neoclassical economics has been dominant for a century or two despite surprisingly little evolution, it’s partly because it suits business interests so well.)

The other strange thing we’ve failed to notice is that the modern obsession with the tax system and regulation of the labour market has crowded out all the economists’ conventional wisdom about what drives productivity improvement over the medium term.

But before we get to that wisdom, a health warning: there’s a famous saying in economics that the sermonisers have stopped making sure you know. It’s that, for economists, productivity is “a measure of our ignorance”.

Just as economists can calculate the “non-accelerating-inflation rate of unemployment”, and kid themselves it’s next to infallible, when you ask them why it’s gone up, or down, all they can do is guess at the reasons, so it is with calculations of productivity. Economists can’t say with any certainty why it’s up or why it’s down. They don’t know.

Even so, in the present opportunistic sermonising, all that the profession thought it knew has been cast aside.

Such as? That productivity improvement is cyclical and hard to measure. Recent quarterly results from the national accounts will probably change as better data come to hand, and the accounts are revised.

It’s true that the measured productivity of labour actually has fallen over the three years to June this year, but it’s likely this is, to a great extent, a product of the wild swings of the pandemic and its lockdowns. As Reserve Bank economists have argued, these effects should “wash out”.

It’s well understood that the main thing that improves the productivity of labour is employers giving their workers more and better machines to work with. But Australia’s level of business investment as a share of gross domestic product is low relative to other rich countries.

Growth in non-mining business investment has declined from the mid-2000s and stagnated over the past decade. It’s grown strongly recently, but it’s not clear how much of this is just tradies taking advantage of lockdown tax concessions to buy a new HiLux ute.

Point is, why do the sermonisers rarely acknowledge that weak business investment spending does a lot to help explain our weak productivity improvement?

Another factor that should be obvious is our recent strong growth in employment, the highest in about 50 years, with many people who employers wouldn’t normally want to employ, getting jobs. This will lower the workforce’s average productivity – but it’s a good development, not a bad one.

Again, why do the sermons never mention this?

Yet another part of the conventional wisdom it’s no longer fashionable to mention is the belief that productivity improvement comes from strong spending – by public and private sectors – on research and development. Have we been doing well on this over the past decade or so? I doubt it.

And, of course, productivity improvement comes from giving a high priority to investment in “human capital” – education and training.

So, why no sermons about the way we’ve gone for a decade or more stuffing up TAFE and vocational education, or the way school funding has given “parental choice” for better-off families priority over the funding of good teaching in public schools?

Too many of those sermons also fail to mention the small fact that all the other developed economies are experiencing similar weakness – suggesting that much of our poor performance is explained by global factors, not the failure of our government.

Related to this, the preachers usually compare our present performance with a much higher 30- or 40-year average, implying our weak performance is something new, unusual and worrying.

Or, we’re told that, whereas productivity improved at an annual rate of 2.1 per cent, over the five years to 2004, it worsened to 0.9 per cent over the six years to 2010, and improved only marginally to 1.2 per cent over the nine years to 2019, before the pandemic.

This is all highly misleading. The fact is that periods of weak improvement are more common than periods of strong improvement, which are rare.

Our period of unusually strong improvement from the late 1990s to the early noughties is paralleled by America’s strong period from 1995 to 2004, which the Yanks usually attribute to rapid productivity improvement in the manufacturing of computers, electronics and semiconductors.

We usually attribute our rare period of strong improvement to the belated effects of the Hawke-Keating government’s program of microeconomic reform. Maybe, but computerisation and the information revolution are a more plausible guess.

Either way, contrary to the sermonisers’ implicit claim that the present period of weak improvement is unusual, it may be closer to the truth that weakness is the norm, interspersed by occasional bursts of huge improvement, caused by the eventual diffusion of some new “general-purpose technology” – the next one likely to be generative AI.

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AI will make or break us - probably a bit of both

Depending on who you talk to, AI – artificial intelligence – is the answer to the rich world’s productivity slowdown and will make us all much more prosperous. Or it will lead to a few foreign mega tech companies controlling far more of our lives than they already do.

So, which is it to be? Well, one thing we can say with confidence is that, like all technological advances, it can be used for good or ill. It’s up to us and our governments to do what’s needed to ensure we get a lot more of the former than the latter.

If all the talk of AI makes your eyes glaze (or you’re so old you think AI stands for artificial insemination), let’s just say that AI is about making it possible for computers to learn from experience, adjust to new information and perform human-like tasks, such as recognising patterns, and making forecasts and decisions.

Scientists have been talking about AI since the 1950s, but in recent years they’ve really started getting somewhere. It took the telephone 75 years to reach 100 million users, whereas the mobile phone took 16 years and the web took seven.

You’ve no doubt seen the fuss about an AI language “bot”, ChatGPT, which can understand questions and generate answers. It was released last year and took just two months to reach 100 million users.

This week the competition minister, Dr Andrew Leigh, gave a speech about AI’s rapidly growing role in the economy. What that’s got to do with competition we’ll soon see.

He says the rise of AI engines has been remarkable and offers the potential for “immense economic and social benefits”.

It “has the potential to turbocharge productivity”. Most Australians work in the services sector, where tasks requiring the processing and evaluation of information and the preparation of written reports are ubiquitous.

“From customer support to computer programming, education to law, there is massive potential for AI to make people more effective at their jobs,” Leigh says.

“And the benefits go beyond what shows up in gross domestic product. AI can make the ideal Spotify playlist for your birthday, detect cancer earlier, devise a training program for your new sport, or play devil’s advocate when you’re developing an argument.”

That’s the optimists’ case. And there’s no doubt a lot of truth to it. But, Leigh warns, “it’s not all upside”.

“Many digital markets have started as fiercely competitive ecosystems, only to consolidate [become dominated by a few big companies] over time.”

We should beware of established businesses asserting their right to train AI models on their own data (which is how the models learn), while denying access to that data to competitors or new businesses seeking to enter the industry.

Leigh says there are five challenges likely to limit the scope for vigorous competition in the development of AI systems.

First, costly chips. A present, only a handful of companies has the cloud and computing resources needed to build and train AI systems. So, any rival start-ups must pay to get access to these resources.

As well, the chipmaker Nvidia has about 70 per cent of the world AI chips market, and has relationships with the big chip users, to the advantage of incumbents.

Second, private data. The best AI models are those trained on the highest quality and greatest volume of data. The latest AI models from Google and Meta (Facebook) are trained on about one trillion words.

And these “generative” AI systems need to be right up-to-date. But the latest ChatGPT version uses data up to only 2021, so thinks Boris Johnson and Scott Morrison are still in power, and doesn’t know the lockdowns are over.

Which brings us, third, to “network effects”. If the top ride-hailing service has twice as many cars as its rival, more users will choose to use it, to reduce their waiting times. So, those platforms coming first tend to get bigger at the expense of their rivals.

What’s more, the more customers the winners attract, the more data they can mine to find out what customers want and don’t want, giving them a further advantage.

This means network effects may fuel pricing power, entrenching the strongest platforms. If AI engines turn out to be “natural monopolies”, regulators will have a lot to worry about.

Fourth, immobile talent. Not many people have the skills to design and further develop AI engines, and training people to do these jobs takes time.

It’s likely that many of these workers are bound by “non-compete” clauses in their job contracts. If so, that can be another factor allowing the dominant platforms to charge their customers higher prices (and pay their workers less than they should).

Finally, AI systems can be set up on an “open first, closed later” business plan. I call it the drug-pusher model: you give it away free until you get enough people hooked, then you start charging.

Clearly, the spread of AI may well come with weak competitive pressure to ensure customers get a good deal and rates of profit aren’t excessive.

Just as competition laws needed to be updated to deal with the misbehaviour of the oil titans and rail barons of 19th century America, so too we may need to make changes to Australian laws to address the challenges that AI poses, Leigh says.

The big question is how amenable to competition the development of AI is. In other, earlier new industries, competition arose because key staff left to start a competing company, or because it made sense for another firm to operate in a different geographic area, or because customers desired a variant on the initial product.

“But if AI is learning from itself, if it is global, and if it is general, then these features may not arise.” If so, concentration maybe more likely than competition.

Get it? If we’re not careful, a few foreign mega tech companies may do better out of AI than we do.

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Globalisation has stopped, but it's not actually reversing - yet

In case you’ve been too worried about your mortgage to notice, the era of ever-increasing globalisation has ended. There’s a backlash against greater economic integration and a risk it will start going backwards, causing the global economy to “fragment”.

The process of globalisation involves the free flow of ideas, people, goods, services and financial capital across national borders, leading to economic integration. But, as a new post on the International Monetary Fund’s blog site reminds us, globalisation is not new, and the process has ebbed and flowed over many decades.

The post charts the progress of globalisation back more than 150 years. Using openness to international trade – measured as global exports plus imports as a proportion of world gross domestic product – it divides that period into five successive eras.

First came the era of industrialisation between 1870 and 1914, when increasing trade between Europe and the “new world” of North America, Argentina and Australia was driven largely by technological advances in transportation – including steel-hulled, steam-driven ships and refrigeration for shipping meat – which lowered the cost of trade.

The laying of undersea cables to improve communication between countries also helped.

Then came the era of wars and protectionism, beginning with the start of World War I in 1914 and finishing with the end of World War II in 1945.

In between came the Great Depression of the 1930s, which was made much worse than it needed to have been by governments trying to protect their domestic industries by using high import duties (“tariffs”) to keep people buying local.

It sounds like a great idea when you do it to other countries. It turns into a stupid idea when they retaliate and do it to you, leaving everyone worse off.

After trade had increased from 30 per cent of world GDP to more than 40 per cent during the era of industrialisation, it had fallen back to about 15 per cent by the end of World War II.

Third came the era of tariff reform between 1945 and 1980. Even before the war had ended, the Allies knew they’d have to fix the world economy. They decided to move to a system of fixed exchange rates and establish the IMF and the World Bank. Most importantly, they set up the General Agreement on Tariffs and Trade (now the World Trade Organisation).

The GATT arranged eight successive “rounds” of multilateral trade negotiations, in which the developed countries agreed to big reductions in their barriers to imports. Thanks to all this, trade doubled from 15 per cent of world GDP to 30 per cent.

This led on to the era of “hyperglobalisation” between 1980 and 2008, with the fall of the Berlin Wall in 1989 and collapse of the Soviet Union, bringing the Cold War to an end.

The eighth, biggest and final, “Uruguay” round of the GATT, in 1994, focused on increasing trade between the developed and developing countries, with many poor economies joining the WTO.

China’s economy began growing rapidly after it was opened up in the late 1970s, and in 2001 it was permitted to join the WTO, hugely increasing its trade.

The era also brought a move to floating exchange rates and deregulation of banking systems, leading to much increased investment between rich and poor countries.

As well, big advances in telecommunications, computerisation and the advent of the internet allowed a surge of trade in digital services, including data processing.

Resulting from all this, trade reached a peak of more than 55 per cent of world GDP in 2008, on the eve of the global financial crisis and the ensuing Great Recession.

The IMF bloggers label the present period, with figures from 2008 up to 2021, the era of “slowbalisation”. To date, those figures bear this out: trade has reached a plateau of about 55 per cent. More recent figures show world trade has largely bounced back from the initial effects of the pandemic’s global coronacession.

It seems the combined effect of the Great Recession and rising protectionist sentiment has stopped trade from continuing to shoot up relative to world GDP, but not caused it to fall back – or not yet.

Less optimistic observers, however, refer to present as the era of “deglobalisation”. They worry that we’re in the early stages of a period of “policy-induced geoeconomic fragmentation”.

It’s not hard to see what’s worrying them. First we had Britain deciding to leave the European Union, then the election of Donald Trump, vowing to “make America great again” by whacking up tariff barriers against the exports of friend and foe alike, and starting a trade war with China.

Now we have the use of trade and other economic sanctions by many countries to punish Russia in its war against Ukraine, which is fragmenting world trade.

US President Joe Biden has toned down his predecessor’s excesses, but not abandoned the trade war. This doesn’t seem to be about protectionism so much as America’s desire not to be overtaken by China as the world’s dominant superpower. In particular, the US wants to stay ahead of the Chinese in advanced digital technology, by denying them access to the latest and best semiconductors.

The risk is that the two could end up dividing the global economy into separate trading blocs, America and its democratic friends versus China and its autocratic friends. This would almost certainly slow the economic growth of both groupings.

And, as economist Dr John Edwards has written, dividing the trading world into good guys and bad guys would not suit us, nor our region. Our exports to China greatly exceed our exports to the US and other close security allies.

And all the East Asian economies – including Japan and South Korea – have China as a major trading partner. For that matter, China and the US are major trading partners of each other.

Fortunately, and despite all the sparring we’ve seen, Edwards and others find no evidence that the US and China have yet started to “decouple”.

Let’s hope economic sense prevails, and it stays that way.

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Digital revolution is leaving economists scratching their heads

There should be a law against holding election campaigns while people are trying to enjoy their Easter break. So let’s forget politics and think about the strange ways the economy is changing as the old industrial era gives way to the post-industrial, digital era.

The revolution in information and communications technology is working its way through the economy, changing the way it works. The markets for digital products now work very differently from the markets for conventional products.

So a growing part of the economy consists of markets that don’t fit the assumptions economists make in their basic model of markets, as Diane Coyle, an economics professor at Cambridge University, explains in her book, Cogs and Monsters.

And the way we measure the industrial economy – using the “national accounts” and gross domestic product – isn’t designed to capture the new range of benefits that flow from digital markets.

Starting at the beginning, the great attraction of the capitalist, market economy is its almost magical ability to increase its productivity – its ability to produce an increased quantity of goods and services from an unchanged quantity of raw materials, capital equipment and human labour.

It’s this increased productivity – not so much the increase in resources used – that explains most of the improvement in our standard of living over the past two centuries.

Where did the greater productivity come from? From advances in technology. From bigger and better machines, and more efficiently organised factories, mines, farms, offices and shops, not to mention better educated and skilled workers.

Particularly in the past 70 years, we benefited hugely from the advent of mass-produced consumer goods on production lines. Economists call this “economies of scale” – the bigger the factory and the more you could produce, the lower the cost of each item.

Although each extra unit produced added marginally to raw material and labour costs, the more you produced, the more the “fixed cost” of building and equipping the factory was averaged over a larger number of items, thus reducing the “average cost” per item.

Decades of exploiting the benefit of economies of scale explain why so many of our industries are dominated by just a few big firms.

But the new economy of digital production has put scale economies on steroids. Coyle says software – and movies, news mastheads and much, much else – is costly to write (high fixed cost) but virtually costless to reproduce and distribute (no marginal cost).

So, production of digital products involves “increasing returns to scale”, which is good news for both producers and consumers - everyone except economists because their standard model assumes returns are either constant or declining.

But another thing that makes the digital economy different is “network effects”, starting with the greatest network, the network of networks, the internet. The basic network effect is that the more users of the network there are, the greater the benefit to the individual user. More increasing returns to scale.

Then, Coyle says, there are indirect network effects. Many digital markets involve “matching” suppliers with consumers – such as Airbnb, Uber and Amazon Marketplace. For consumers, the more suppliers the network attracts, the better the chance of quickly finding what you want. But, equally, for suppliers, the more customers the network attracts, the easier it is to make a sale. Economists call these digital networks “two-sided platforms”. The owner of the platform sits in the middle, dealing with both sides.

So, yet more benefits from bigness. And that’s before you get to the benefits of building, mining and sharing large collections of data.

All these benefits being so great, it’s not hard to see why you could end up with only a couple – maybe just one – giant network dominating a market. Welcome to the world of Google, Facebook, Apple, Amazon and Microsoft.

In their forthcoming book, From Free to Fair Markets, Richard Holden, an economics professor at the University of NSW, and Rosalind Dixon, a law professor at the same place, note that a number of leading lights have proposed breaking up these huge tech companies, in the same way America’s big telephone monopoly and interlocking oil companies were broken up last century.

But, the authors object, in most of these markets the power of these giants stems from the “network externalities” we’ve just discussed.

“Unlike traditional markets, when the source of market power is also the source of consumer harm, in these markets the source of market power is also what consumers (and producers, in the case of two-sided platforms) value – being connected with other consumers and producers,” they write.

“The key driver of the value that these firms create is precisely the network externalities that they bring about. Facebook is valuable to users because lots of other users are on Facebook . . .

“Google is a superior search engine because in performing so many searches, machine learning allows its algorithm to get better and better, making it a more desirable search engine.”

So, the driving force that leads to these markets having one dominant player is also the force that creates economic value. “Breaking up the large players will stop there being just a few large players, but it will also stop there being nearly as much economic value created,” they say.

Research by Holden, Professor Luis Rayo and the Nobel laureate Robert Akerlof has found that markets with network externalities tend to have three features. First, the firm that wins the initial competition in the market ends up with most of the market.

Second, it’s difficult to become a winning firm, and success is fragile. For instance, Microsoft has had little success getting its search engine Bing to take business from Google. And Netscape was once dominant in the browser market, but suddenly got supplanted.

Third, winners can’t go to sleep. They must constantly innovate and seek to raise their quality.

This makes the tech markets quite different from conventional markets like oil or even old-style networks like railways.

Economists’ efforts to get a handle on the new economy continue.

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Here's a novel idea: Australia needs more competition, not less

Business has many tired ideas for reforming the economy and improving productivity, most of which boil down to: cut my tax and give me more power to keep my wage bill low. But a veteran econocrat has proposed a new and frightening reform: make our businesses compete harder for our custom, thus making it harder for them to raise their prices.

Treasurer Josh Frydenberg has asked the Productivity Commission to undertake a five-yearly review of our (dismal) productivity performance. And this week Rod Sims, who’s departing after 11 years heading the Australian Competition and Consumer Commission, offered a few helpful hints in a speech to the National Press Club.

Sims says “the Australian economy suffers from high levels of market concentration [markets dominated by a few big firms] to the detriment of consumers, small business and productivity”.

He argues that the pandemic-related supply shortages and logistics problems we’re facing are worsened by market concentration in so many areas and by our infrastructure bottlenecks.

“We need to address this through competition law, to prevent anti-competitive abuses of market power, and through general infrastructure reform,” he says. He’s referring mainly to road, rail, air and sea transport facilities, and also to utilities – electricity, gas and water.

Australia’s infrastructure is generally high cost, he says, compared with other countries. “Why do we keep privatising assets and claiming success when huge amounts are paid for the asset?”

My answer: when state Treasuries are run by bankers rather than econocrats, that’s what they think they’re supposed to be doing.

Sims says that often, “these huge prices are the result of closing off competition, or because a monopoly was deliberately sold without any regulation of the prices that can be set for users who have no alternative but to use the monopoly asset”.

“Such behaviour can dramatically affect existing users and could be considered a continuing tax on the community,” he says.

Governments need to sign up to a checklist before infrastructure assets are sold to avoid provisions which restrict competition and to ensure there is appropriate regulation where monopoly or significant market power will exist after the sale to private interests, he says.

“Let’s acknowledge this issue and fix it so that Australia can avoid even higher priced infrastructure in future.”

Another infrastructure challenge is ensuring the regulatory arrangements for the National Broadband Network are appropriate.

“After [the federal government] spending $50 billion on the NBN, the objective must not be a commercial return on the [$50 billion] sunk investment. It must be making the best use of this great asset.

“The prices that allow the NBN to get a commercial return on all its outlays, and the prices that make best use of this expensive asset, are very likely quite different,” he says.

We all saw the benefit of having the NBN completed in time for the pandemic lockdowns. That’s just a taste of the benefits if we get the NBN’s pricing right. Prices must allow the NBN to keep investing as needed, but must also see optimum use made of the network.

That is, the goal should be maximising the network’s benefit to the whole economy, not creating a new business that can exploit the pricing power that usually goes with a monopoly network, then selling it off to the highest bidder (or continuing to own it while overcharging customers).

Another area where we’re not getting enough competition, are paying prices that are too high (often in ways that aren’t visible) and are crimping productivity improvement is “digital platforms”.

Sims says we have an internet dominated by a few gatekeeper companies: Google has 95 per cent of searching activity, Facebook dominates social media, and Google and Apple dominate the app market, particularly on mobile devices.

“I am proud that the ACCC is at the forefront of world efforts to identify the harms from digital platforms and potential solutions to them,” he says.

While it’s true that these giants innovated their way to success - bringing many benefits to ordinary internet users – it’s equally true they also acquired a huge array of companies that could have been competitors, which has extended their reach and cemented their power.

They also engage in many activities, from “product bundling” (where to get the ones you want, you have to pay for stuff you don’t want) to “self-preferencing” (where they put their own products at the top of a list, and rival firms’ products at the bottom). Over time, this has lessened competition in various important digital markets.

The digital giants also have access to, and control, a massive amount of data, which has seen harms ranging from that seen with Cambridge Analytica, to profiling people so as to maximise sales by exploiting consumers’ vulnerabilities.

Then there’s the many examples of inadequate competition in banking. Sims quotes just three. First, the price of the most important financial product, a home mortgage, is unknowable without huge effort and cost, which benefits banks and harms borrowers.

The still-being-rolled-out “consumer data right” (that is, it’s your data so you should be able to have it forwarded to a rival business) should help this a lot. And Sims wants consumers to be continually informed by a “prompt” of what typical borrowers are paying, so they know when to start shopping around.

Second, to reduce “debanking” – where banks find excuses to refuse to move money that has been arranged through the new “fintechs” and money remitters – the government should set up a scheme these digital non-banks can use to prove their controls are adequate to detect money laundering.

Third, now the digital giants are getting into the now largely cashless world, outfits such as Apple Pay must be stopped from preventing other providers of digital wallets making use of its “near field technology”.

Funny how it’s never occurred to the Business Council and other business lobby groups wringing their hands over weak productivity that an obvious solution to the problem is to make firms compete harder for their profits.

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Beware of governments using algorithms to collect revenue

A great advantage of having children and grandchildren is that they can show you how to do things on the internet – or your phone – that you can’t for the life of you see how to do yourself. But a small advantage that oldies have over youngsters is that we can remember how much more clunky and inconvenient life used to be before the digital revolution.

When you had to get out of your chair to change the telly to one of the other three channels. When you spent lunchtimes walking to companies’ offices to pay bills. When you had to visit your own branch of a bank to get cash or deposit a cheque.

When you had to write and post letters, rather than dashing off an email or text message. When we were paid in notes and coins rather than via a direct credit. When buying something from a business overseas was too tricky to ever contemplate.

Computers connected by the internet are transforming our world, making many of the things we do easier, more convenient, better and often cheaper. Businesses are adopting new technology because they see it as a way to cut costs, compete more effectively, attract more customers and make more money.

Governments have been slower to take advantage of digitisation, websites, artificial intelligence and machine learning. But there’s a lot to be gained in reduced red tape, convenience for taxpayers, efficiency and cost saving, and now governments at all levels are stepping up their use of new technology – which most of us would be pleased to see.

But, as with so many things, new technology can be used for good or ill. The most egregious case of government misuse of technology was surely Centrelink’s “automated income compliance program” aka robo-debt.

Here, a dodgy algorithm was used to accuse people on benefits of understating their income over many years and to demand repayment. Despite assurances by the two ministers responsible – Christian Porter and Alan Tudge – that all was fair and above board, huge anxiety was caused to many unjustly accused poor people.

The Coalition government obfuscated for years before a court finally ruled the program unlawful and the government agreed to return $1.8 billion. For a scheme intended to cut costs, it was an immoral own goal.

But last week the NSW Ombudsman, Paul Miller, revealed that something similar had been going on in NSW. Between 2016 and 2019, the state’s debt-collection agency, Revenue NSW, unlawfully used an automated system to claw back unpaid fines from financially vulnerable people, in some cases emptying bank accounts and leaving them unable to buy food or pay rent.

The automated system created garnishee orders, requiring banks to remove money from debtors’ bank accounts, without the debtors even being informed. The computer program took no account of any hardship this would impose.

Between 2011 and 2019, the number of garnishee orders issued by Revenue NSW each year jumped from 6900 to more than 1.6 million. The Ombudsman began investigating after receiving “a spate of complaints from people, many of them financially vulnerable individuals, who had discovered their bank accounts had been stripped of funds, and sometimes completely emptied.

“Those people were not complaining to us about the use of automation. They didn’t even know about it.”

As usually happens, we find out about this long after the problem has been (apparently) rectified. Unlike the feds, the NSW Revenue office agreed to modify its process in 2019, so that garnishee orders are no longer fully automated.

People identified as vulnerable were excluded from garnishee orders. And a minimum amount of $523.10 (!) is now left in the garnished account.

But Revenue NSW didn’t seek advice on whether the original scheme was legal, so the Ombudsman did. It wasn’t. The lawyers say the law gives the right to extract money from people to an “authorised person” – not to a machine.

So, two isolated incidents – one federal, one state – and everything’s now fixed? Don’t be so sure. Miller says that, in NSW, other agencies are known to be using machine technologies for enforcement of fines, policing, child protection and driver licence suspensions.

How do we know it isn’t happening – or will happen – in other states?

NSW Finance Minister Damien Tudehope said garnishee orders were a last resort after a person had been contacted multiple times in writing and given options about overdue fines.

“For those who have chosen to ignore our notices and simply don’t want to pay, the community has an expectation we take action to recover what is owed,” he said.

Yes, but few of us want governments riding roughshod over people who can’t pay because they’re on poverty-level social security benefits.

I leave the last word to Anoulack Chanthivong, NSW opposition finance spokesman: “The pursuit of economic efficiency through artificial intelligence should never come at the expense of treating our more vulnerable citizens with dignity and decency.

“Governments at all levels are meant to serve our community and make their lives better, not find unlawful ways to make them worse.”

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Working from home would be back to the future

By now it seems cut and dried. The pandemic has taught us to love the benefits of working from home and stopped bosses fearing it, so we’ll keep doing it once the virus has receded and the kids are back at school. Well, maybe, maybe not. Any lasting change in the way we work is likely to be evolutionary rather than revolutionary.

Productivity Commission boss Michael Brennan and his troops have been giving the matter much thought and, as he revealed in a speech last week, such a radical change in the way we work would be produced by the interaction of various conflicting but powerful forces.

After all, it would be a return to the way we worked 300 years ago before the Industrial Revolution. Then, most people worked from home as farmers, weavers and blacksmiths and other skilled artisans. And, don’t forget, by today’s standards we were extremely poor.

What’s made us so much more prosperous? Advances in technology. But technology is the product of human invention. That invention could have pushed our lives in other directions.

What underlying force pushed us in the direction it did? As the Productivity Commission boss was too subtle to say, our pursuit of improved productivity.

Productivity isn’t producing more, it’s producing more with less. In particular, producing more of the goods and services we love to consume using less labour. Why among the three “factors of production” – land and its raw materials, capital equipment and labour – is it labour we’ve always sought to minimise?

Because we run the economy to benefit ourselves, and it’s humans who do the labour. We’ve reduced physical labour, but now automation allows us to reduce routine mental labour.

(While we’re on the subject, note this. Many people think automation destroys jobs. But in 250 years of installing ever-better “labour-saving technology” we’ve managed to increase unemployment only to 6 per cent or so. That’s because automation doesn’t destroy jobs, it changes and moves them. From the production of physical goods to the delivery of human services. In the process, it’s made us hugely better off.)

It was the Industrial Revolution that increasingly drove us to the centralised workplace. Initially, the factory and the mine, then the office.

The move to most people working in a central location was driven by economic forces. Businesses saw the benefits – to them and their customers – of combining labour with large and expensive machinery, powered by a single source. Initially, steam.

“The factory provided a means for bosses to co-ordinate activity in real time, supervise workers and it also provided an efficient way to share knowledge – as did the office,” Brennan says.

So the central workplace reduced the cost of combining labour and capital, but did so by imposing transport costs – mainly on workers who had to get themselves from home to the central location and back.

For most of the 20th century, however, it got ever-cheaper to move people around, via steam, electricity, the internal-combustion engine and the aeroplane. So advances in transport technology reinforced the role of the central workplace.

For about the past 30 years, however, the cost of moving people around has stopped falling. “We seem to have hit physical limits on speed; and congestion has meant that today it takes longer to move around our cities than was the case a few decades ago,” Brennan says.

This, of course, is why we fancy the idea of continuing to work from home. It’s only advances in computing and telecommunications technology that have made this possible. The cost of moving information has plummeted, while the cost of moving workers – in time and discomfort – has gone up.

So, could it be that modern communications technology is set to drive us back to our homes?

Perhaps. But remember this. While the tiny proportion of people working from home has hardly budged over the past two decades, our capital city CBDs have become more significant as centres of economic activity and as engines of productivity improvement.

Here’s the catch. At the same time as information technology was improving, and the cost of communicating over distance was falling, the nature of work was changing. As machines have replaced routine tasks, modern jobs have come to require more open-ended decision-making, critical thinking and adaptability.

Experts think these quintessentially human skills are best developed and honed through face-to-face interactions, such as the serendipitous encounter or the tacit knowledge we absorb through observing those around us.

Get it? That many of us have come to prefer working from home (I’ve been doing it since 1990) is just one factor that happens to be pulling us in the direction of home. Other factors will keep pulling us into the office. Expect a lot of businesses experimenting with different mixes of the two.

Economic history suggests that what evolves will be the combination that maximises our productivity. Not just because bosses want to make bigger profits, but also because most people like a rising standard of living.

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How inflation became a big problem, but has disappeared

Treasury Secretary Dr Steven Kennedy observed this week that there’s been “a fundamental shift in the macro-economic underpinnings of the global and domestic economies, the cause of which is still not fully understood”. He’s right. And he’s the first of our top econocrats to say it. But he didn’t elaborate.

This week we got further evidence of that fundamental shift. The Australian Bureau of Statistics’ consumer price index for the September quarter showed an annual “headline” inflation rate of 0.7 per cent and an “underlying” (that is, more reliable) rate of 1.2 per cent.

This is exceptionally low and is clearly affected by the coronacession, as you’d expect. But there’s more going on than just a recession. Since 1993, our inflation target has been for annual inflation to average 2 to 3 per cent. For the six years before the virus, however, it averaged 1.6 per cent. And most other rich countries have also been undershooting their targets.

So, part of the “fundamental shift” in the factors underpinning the global economy is that inflation has gone away as a significant problem. But why? As Kennedy says, these things are “still not fully understood”. Some economists are advancing explanatory theories, which the other economists are debating.

Former Reserve Bank governor Ian Macfarlane, who has form for being the first to spot what’s happening, offered his own explanation of the rise and fall of inflation in a recent Jolly Swagman podcast.

Macfarlane says that, though every developed economy’s experience is different, they’re all quite similar. If you stand well back and look at the rich countries’ experience over the past 60 years, he says it’s not too great a simplification to say that two phases stand out: inflation rose in the first phase to reach a peak in the mid-1970s to early 1980s, but then fell almost continuously until we reached the present situation where it’s below the targets set by central banks.

In our case, we had double-digit inflation in the ’70s and rates of 5 to 7 per cent in the ’80s, then a long period within the target range until about six years ago. Since then it’s been below the target “despite the most expansionary monetary policy [the lowest interest rates] anyone can remember”.

So how is this experience of roughly 30 years of rising inflation, then 30 years of falling inflation explained? Macfarlane thinks there are about half a dozen reasons for the worsening of inflation in Australia.

For a start, the growth of production and employment during the 30-year post-war Golden Age was stronger than any period before or since. We had high levels of protection against imports, with little or no competition from developing countries.

We had a strong union movement, confident that in pushing for higher wages it wasn’t jeopardising workers’ job prospects. We had a centralised system for setting wages, with widespread indexation of wages to the consumer price index.

Our businesses took a “cost-plus” approach to their prices. If wages or the cost of imported components rose, this could be passed on to customers, confident your competitors would be doing the same. That is, firms had “pricing power”.

Finally, businesses’, unions’ and consumers’ expectations about how fast prices would rise in future were quite low at the start of the period, but they picked up and, by the end, had become entrenched at a high rate.

“This macro-economic environment was clearly conducive to rising inflation, and it took one policy error to push it over the limit,” Macfarlane says.

Under the McMahon government – predecessor of the Whitlam government – fiscal policy was made expansionary even though the inflation rate was already 7 per cent. Monetary policy was eased, with interest rates remaining below the inflation rate. And the centralised wage-fixing system awarded 6 or 9 per cent pay rises.

So, that’s how we acquired an inflation problem. What changed in the second 30-year period of declining inflation? Macfarlane thinks “the defining feature of the later period was that, in the long struggle between capital and labour, the interests of capital took precedence over those of labour”.

That is, the bargaining power of labour collapsed. In most countries the labour share of gross domestic product has declined, with the profits share increasing. Wage growth has been restrained, union membership has shrunk and the inequality of income and wealth has increased.

“These features have been most pronounced in the US, but many other countries, including Australia, have shown most of the same signs,” he says.

Two main developments account for this change. First, globalisation. The rapid growth of manufactured exports from China and the developing world pushed down consumer prices. More importantly, businesses and workers in the rich world realised that firms or whole industries could be shifted to countries where wages were lower.

Businesses had lost pricing power and sought to maintain profits by cutting costs and reducing staff levels. Union members became more concerned with saving their jobs than pushing for higher wages.

Second, labour-saving technological advance. In manufacturing, sophisticated machines started replacing workers. In the much bigger services sector, advances in information and communications meant that armies of state managers, regional managers and other middle management were no longer needed. Clerical processes were automated. Call centres were cheaper than a network of offices. Customers could buy on the internet, without the need for shop assistants.

As the period of high inflation passed into distant memory, Macfarlane says, inflationary expectations fell. Inflation expectations – whose importance comes because they tend to be self-fulfilling – change very slowly. It took decades for them to rise in the earlier period and, now, after nearly three decades of moderate and low inflation, it will take a long time before higher inflationary expectations are rekindled.

I see much truth in Macfarlane’s explanation. But it certainly means there’s been a “fundamental shift” in the factors bearing down on the economy – the implications of which we’re yet to fully realise, let alone fix.

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Technology is amazing, but human nature is unchanging

When momentous events such as the coronavirus pandemic occur, it's tempting to conclude they'll change our lives forever. Even if we don't think it, you can be sure there'll be some overexcited journalists saying it. Just as there were after the attack on the Twin Towers on 9/11 in 2001.

Even then I was too old to believe it would "change our lives forever" and – although it did have lasting effects on international relations and our fear of terrorism – it didn't really.

This time people are telling us we'll all be working from home (with city office blocks and streets turning into ghost towns), doing our shopping online, learning online, seeing doctors online, and no longer doing business travel.

Somehow, I doubt it will be that radical. But I don't doubt there'll be change in all those directions. Most of them were already happening as part of the continuing digital revolution, and this will accelerate those trends.

The revolution's usual pattern is to bring modest benefits – greater "functionality" (machines that do more and better tricks) and convenience – to an industry's customers, while turning the industry on its head, with considerable disruption to the lives of many of its workers.

There was a time when watching television meant seeing only what the few available channels happened to be showing at the time. These days, recorders and catch-up apps and a multitude of free-to-air and for-the-small-fee channels and streaming video have given us vastly more choice.

This has meant huge upheaval for the industry, but improved our lives only to a small extent – something we've soon come to take for granted.

Some people (and not just Victorians) are finding it hard to imagine the pandemic will ever be over. But, though we can't be sure when, it will end. And when it does, far more aspects of the way we live and work will go back to the way they were than will change forever.

Truth be told, and unless we do a lot more to correct it, the biggest and baddest continuing effect of the pandemic will be on the careers of young people leaving education during the recession and what looks like being a long and weak recovery.

Staying serious, we can expect more concern about problems in health than in education. More concern about physical health than mental health. More concern about the problems of the old than those of the young.

Nothing new about any of that – except that Scott Morrison's heroic condemnation of those on his own side of politics suggesting that the lives of the elderly should have been "offered up" in the interests of the economy sits oddly with his and all federal politicians' tolerance of decades-long neglect and misregulation of aged care.

(As economists make themselves unpopular by pointing out, every time politicians decide to spare taxpayers the expense of fixing a level-crossing or in some other way saving "just one person" they are implicitly putting a dollar value on human life. They do so on our behalf and we rarely tell them to stop doing it. The term "cognitive dissonance" comes to mind.)

But I'm determined to keep it light this week, so on with happy chat about the pros and cons of new technology.

It's worth remembering that advances in digital technology have made the lockdown and social distancing tolerable – indeed, doable – in a way that wouldn't have been possible 20 years ago. Far more of us work as "symbolic analysts" (people who spend all day making changes on a screen) these days. Get access to all the office's programs on your laptop at home? Easy. Zoom to endless and unending meetings? Feel free.

The virus is likely to hasten technology-driven change because the crisis has broken through our fear of the new and unfamiliar. Both workers and bosses now understand both the pros and the cons of working from home relative to working from work.

We've tried buying groceries online. Doctors, departments of finance and patients have overcome their hang-ups about telemedicine. Online learning suits uni students better than school pupils.

But all these things do have their advantages and disadvantages. And most of the disadvantages are social. For the human animal, social distancing is a deeply unnatural act. We get a lot of our emotional gratification from face-to-face contact.

We communicate more efficiently and we learn things we wouldn't otherwise learn that help us do our job better. Relationships with suppliers, customers and consultants work better when we come to know and like each other.

So I think we'll do more digital remote working, but not turn our working lives over to it. Surveys show most people would like to work from home some days a week, but not all week. Business people may do less travel between capital cities – it could easily become the latest business cost-cutting fad – but it would be amazing if executives stopped wanting to shake hands with the people they deal with.

Technology can change what we do, but it won't change human nature.

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Star pupil Philip Lowe gives tips on why inflation is so low

Reserve Bank governor Philip Lowe started his study of economics at high school in Wagga Wagga and finished it with a PhD from the Massachusetts Institute of Technology. Much thanks to his teacher, Mrs King, whose teaching style convinced him economics was interesting as well as important.

The great attraction of high school economics is its emphasis on linking theory to current events.

According to a speech he gave last week, when Lowe did the HSC in 1979, the standard exam question was: why does Australia have both high inflation and high unemployment ("stagflation") and what’s the government doing about it?

In those days there was much interest in the "misery index", which adds the inflation rate to the unemployment rate. We got to peaks well above 20 per cent. Today, however, it’s below 7 per cent.

As the Australian Bureau of Statistics advised this week, the consumer price index rose by just 1.6 per cent over the year to June. Which means it’s been below the Reserve’s inflation target of "between 2 and 3 per cent, on average, over the medium term" for almost five years.

So Lowe’s guess is that, these days, exam questions are likely to ask: why is inflation so low at the same time as unemployment is also low – and what’s the government doing about it?

Just to be of help, he told us how he’d answer the question – which is one of interest and importance to all of us, not just youngsters preparing for their finals.

He started by noting that very low inflation has become the norm in most economies. At present, three-quarters of advanced economies have an inflation rate below 2 per cent.

There’s no single answer, he says, but there are three factors that, together, help explain what’s happened.

First, the credibility of the monetary "frameworks" that central banks eventually adopted when, in the second half of the 1970s, they realised inflation was way too high and needed to be got under control.

It wasn’t until the early '90s that our Reserve Bank adopted its present target for inflation which, as Lowe says, helped cement low inflation “norms” in the economy. In econospeak, it provided an anchor for business and unions’ expectations about how much prices were likely to rise over the next year or two.

"Many people understand that if inflation were to pick up too much, the central bank would respond to make sure the pick-up was only temporary,” Lowe says.

It would do so by raising interest rates and so discouraging borrowing and spending, of course. Economists call this the "monetary policy reaction function".

(It’s one of the reasons for the old view among economists that attempts to use the budget to stimulate demand by cutting taxes or increasing government spending wouldn’t achieve much. The central bank, fearing the stimulus would push up inflation, would react by raising interest rates and so stymie it. In the new world of continuing weak demand and too-low inflation, however, central banks are most unlikely to react to budgetary stimulus in such a way, meaning the new view is that budgetary stimulus is very effective.)

Has inflation targeting worked? Well, annual inflation has averaged 2.4 per cent since the target was adopted, so it certainly seems to have.

The second part of Lowe’s explanation for very low inflation is that spare capacity to produce goods and services (including spare workers who are unemployed or under-employed) in many advanced economies means there’s little upward pressure on prices.

That certainly seems the case in Australia. Our unemployment rate could go a lot lower than its present 5.2 per cent without causing wages to take off – especially with our under-employment rate of 8.3 per cent.

Our labour market seems to be more flexible – and less inflation-prone - than it used to be.

The third part of his explanation is that changes in the structure of the economy caused by technology and globalisation seem to be keeping prices low.

For one thing, digitisation and globalisation seem to be lowering the cost of producing many goods. The entry of China and other emerging economies into the global trading system has added hundreds of millions of factory workers to the global market.

The prices of manufactured goods in the advanced economies have barely increased over the past couple of decades.

For another thing, globalisation and advances in technology are making markets more contestable and increasing competition. This is extending beyond manufacturing to almost every corner of the economy, including the services sector.

Historically, most services couldn’t be traded across national borders. But globalisation – driven mainly by advances in information and communication technology – means many services can now be delivered by somebody in another country.

Examples include preparation of architectural drawings, document design and publishing, and customer service roles (a nice name for call centres). As well, many tasks such as accounting and payroll have been automated.

The internet and its digital “platforms” have revolutionised services such as retail, media and entertainment, and transformed how we communicate, and search for information and compare prices.

"These changes are having a material effect on pricing, with services price inflation lower than it once was. Many firms know that if they don’t keep their prices down, another firm somewhere in the world might undercut them," Lowe says.

"And many workers are concerned that if the cost of employing them is too high, relative to their productivity [an important qualification], their employer might look overseas or consider automation."

More broadly, using the internet for better “price discovery” keeps the competitive pressure on firms.

The end result is a pervasive feeling of more competition. And more competition normally means lower prices.

What’s the government doing about low inflation and the deficient demand that is part of its cause?

Well, if you mean the elected government, the short answer is: not nearly enough. Especially when you remember how little scope the Reserve Bank has left to cut interest rates.

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Endless fights over money don’t improve education results

One of the few things both sides agree on in this election campaign is that we must get education right. A highly educated and well-trained workforce is our best insurance that all the benefits that digital disruption brings don’t come at the cost of many people unable to find decent jobs.

As a rich nation, our workers are highly paid. That’s not bad, it’s good. But it does mean we have to ensure our workers continue being equipped with the knowledge and skills that make their labour valuable - to local employers and to the purchasers of the goods and services we export.

One thing it doesn’t mean is that all our youngsters should go to university. There will be plenty of well-paid, safe, interesting jobs for the less academically inclined, provided they’re equipped with the valuable technical and caring skills provided by a healthy vocational education and training sector.

A top-notch technical education system will also be key to achieving something we’ve long just rabbited on about: lifelong learning. Being able to update your skills for your occupation’s latest digital whiz-bangery, or quickly acquire different skills for a job in a new industry with better prospects than the one that just ejected you.

But while we’re emphasising education’s instrumental importance to maintaining our material standard of living, we should never lose sight of its intrinsic value to our spiritual living standard. Education for its own sake. Because it satisfies humans’ insatiable curiosity about the world – even the universe – we live in.

We need to get education and training right at every level, from childcare (these days renamed ECEC - “early childhood education and care”), preschool, primary and secondary school, vocational education and training, and university.

To me, our greater understanding of the way tiny brains develop combines with common sense to say that, in our efforts to get every level of education up to scratch, we should start at the bottom and work up.

The better-equipped kids are when they progress from one stage to the next, the easier it is for that next stage to ensure they thrive rather than fall behind.

On childcare, the Coalition did a good job of rationalising the feds’ two conflicting childcare subsidies, but Labor is promising a lot more money for childcare, including phasing in much better pay for (mainly female) better-educated childcare workers.

The Coalition has achieved universal preschool for four-year-olds and, in the budget, extended that funding for a further two years. Labor has topped that, promising permanent funding arrangements and extension of the scheme to three-year-olds, as most other rich countries do.

Let’s be frank: because Labor plans to increase, rather than cut, the tax on high income-earners, it has a lot more money to spend on all levels of education (plus a lot of other areas).

It’s certainly promising to spend more on schools. The Coalition’s great achievement has been to introduce its own, better and somewhat cheaper version of businessman David Gonski’s needs-based funding of schools – which it immediately marred by doing a special deal with Catholic schools.

Labor’s promising to return to its earlier Gonski funding levels (but, hopefully, not to its earlier commitment that no rich school would lose a dollar).

It’s often claimed we spend a lot on schools relative to other countries, but the Grattan Institute’s schools expert, Dr Peter Goss, says that, when you allow for our younger population, only the Netherlands and the United States spend less than we do among nine other comparable rich countries.

International testing shows our 15-year-olds’ scores for maths, science and reading are each below the average for those countries. On maths, our score of 524 in 2003 had dropped to 494 by 2015.

For science, our gap between the top and bottom students – a measure of fairness - is wider than for the others, bar Canada, South Korea, Japan and even Britain.

Which demolishes the claim that we’re pouring more money into schools but getting worse results. What’s true is that our spending is below average and our results are also below average – and getting worse.

So, do we need to spend a lot more? No, not a lot more now we’ve gone a long way towards redistributing funding favour of needy (mainly public) schools full of kids with low income, low educated parents.

The feds and, more particularly, the states have more to do to re-align funding between advantaged non-government schools and their own disadvantaged public schools.

Once disadvantaged schools are getting their full whack of needs-based funding, however, we can end the eternal shootfight over money and move to the more important issue of ensuring the money's better spent.

Much can be done to help teachers move to more effective ways of teaching, making schools less like a production line and giving more attention to individuals, many of whom have trouble keeping up, while some are insufficiently challenged.

But, Goss says, this is mainly a job for the state governments, and the feds should avoid trying to backseat drive. The feds would help more by obliging the universities to do a much better job of selecting and preparing future teachers.

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Not sure what the economy's up to? Nor are the experts

There are times when the rich world’s macro-economists think they’ve got everything figured, and times when they know they haven’t. The latter is where we are now, with the entire profession scratching its head and wondering what’s causing the economy to behave as it is.

The last time economists thought they had it tabbed was between the mid-1980s and the mid-2000s. The world economy was growing so smoothly they decided we’d entered the Great Moderation and began patting themselves on the back.

Always a bad sign. Next thing we knew the global financial crisis had arrived and with it the Great Recession.

But it’s now a decade since the start of that recession, and it’s clear the advanced economies aren’t back to anything like what they were – even, despite appearances, the American economy.

The problem has various symptoms, but it boils down to slow economic growth, which boils down further to much slower rates of productivity improvement than we’ve been used to. This is surprising when you consider how much digital disruption we’re seeing. Isn’t that aimed at improving productivity?

So why is it happening? That’s anybody’s guess. A host of possible explanations is being advanced and debated. It could be another decade before a new conventional wisdom emerges.

I’ve written before about the thesis that the digital revolution won’t boost productivity the way earlier waves of general-purpose technologies did, about the thesis of “secular stagnation” and yet another idea that the main trouble is decades of weak business investment.

But last week Dr Luci Ellis, a Reserve Bank assistant governor, offered her own thoughts on yet another possible piece in the jigsaw puzzle. Productivity is generated by firms, but Ellis notes that, both in Australia and abroad, the evidence suggests that levels of productivity vary widely between firms, even within the same narrowly defined industry.

“Firms that are highly productive – so-called superstar firms – tend to grow faster, grow employment faster, and pay better than firms that are a long way from the frontier of productivity”, she says.

But there’s a problem. Because these superstar firms are more productive than average, they gain market share at the expense of less-productive competitors.

The leading firms could start moving further and further ahead of the pack.

Those that lag behind would then find it harder and harder to catch up. The result could be that markets become more concentrated.

“The market leader begins to reap monopoly profits, which isn’t good for consumers and might not be good for long-run innovation and [society’s] welfare”, she says.

But must the laggard firms never catch up? That may depend on why so many firms are lagging. If it’s because they lack managerial ability, it ought to be possible for them to copy the leaders’ superior approach or even poach their rival’s managers. If so, this would lift the whole industry’s – and the nation’s – productivity.

But what if the laggards have lower productivity because they aren’t adopting the latest technology the way the superstars are? There’s evidence this is the case in other advanced economies, but Ellis says we don’t yet know if it’s true in Australia.

If this superstar pattern has arisen only recently, it could be something to do with the nature of developments in digital technology and their ease of adoption.

Previous waves of general-purpose technologies, such as electricity or the earlier round of computerisation, had the benefit of reducing the level of skill needed to operate them, whereas innovations such as machine learning and artificial intelligence seem to have a very different character, she says.

“Using machine learning and other emerging techniques to automate routine business processes seems to involve specialist skills and, often, PhD-level training in statistics or computer science. These skills are much rarer and take longer to develop than those required for the jobs that are thereby replaced.

“That doesn’t mean it’s impossible, but it could take a long time,” she says.

And get this: if leading-edge technologies are (at present, anyway) unusually costly or difficult to adopt, they become a kind of barrier to entry protecting the firms that are already using those technologies.

That would be a worry if lagging firms never caught up. And if incumbents never face rivals, they’re more likely to become complacent. “Innovation could slow down, and growth in living standards with it”, she concludes.

So, is this the big reason productivity improvement has slowed throughout the advanced economies? Far too soon to say.

But it makes an important point: the problem, and the solution, lie in the hands of our big companies.

Governments may have a role in spending more – and more wisely – on education and training, but giving up a lot of revenue to cut the rate of company tax isn’t likely to make much difference.

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